Muhammad Saqib

1.1k total citations · 1 hit paper
29 papers, 432 citations indexed

About

Muhammad Saqib is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Ocean Engineering. According to data from OpenAlex, Muhammad Saqib has authored 29 papers receiving a total of 432 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 12 papers in Artificial Intelligence and 5 papers in Ocean Engineering. Recurrent topics in Muhammad Saqib's work include Video Surveillance and Tracking Methods (9 papers), Anomaly Detection Techniques and Applications (7 papers) and Advanced Neural Network Applications (5 papers). Muhammad Saqib is often cited by papers focused on Video Surveillance and Tracking Methods (9 papers), Anomaly Detection Techniques and Applications (7 papers) and Advanced Neural Network Applications (5 papers). Muhammad Saqib collaborates with scholars based in Australia, Pakistan and Saudi Arabia. Muhammad Saqib's co-authors include Michael Blumenstein, Nabin Sharma, Sultan Daud Khan, Michael Blumenstein, Chin‐Teng Lin, Naveed Akhtar, Saeed Anwar, Humza Naveed, Muhammad Usman and Shi Qiu and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Biological Conservation.

In The Last Decade

Muhammad Saqib

24 papers receiving 407 citations

Hit Papers

A Comprehensive Overview of Large Language Models 2025 2026 2025 20 40 60
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A Comprehensive Overview of Large Language Models
    2025 72 citations Humza Naveed, Asad Ullah Khan et al. ACM Transactions on Intelligent Systems and Technology profile →

Peers

Muhammad Saqib
Payal Mittal India
Rin-ichiro Taniguchi Japan
Tobias Senst Germany
Адилхан Сымагулов Kazakhstan
Xiaotian Wang China
Duong-Van Nguyen Germany
A. Mittal India
Misbah Ahmad South Korea
Payal Mittal India
Muhammad Saqib
Citations per year, relative to Muhammad Saqib Muhammad Saqib (= 1×) peers Payal Mittal

Countries citing papers authored by Muhammad Saqib

Since Specialization
Citations

This map shows the geographic impact of Muhammad Saqib's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Muhammad Saqib with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Saqib more than expected).

Fields of papers citing papers by Muhammad Saqib

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Muhammad Saqib. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Muhammad Saqib. The network helps show where Muhammad Saqib may publish in the future.

Co-authorship network of co-authors of Muhammad Saqib

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Saqib. A scholar is included among the top collaborators of Muhammad Saqib based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Muhammad Saqib. Muhammad Saqib is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Naveed, Humza, Asad Ullah Khan, Shi Qiu, et al.. (2025). A Comprehensive Overview of Large Language Models. ACM Transactions on Intelligent Systems and Technology. 16(5). 1–72. 72 indexed citations breakdown →
2.
Saqib, Muhammad, et al.. (2025). Text Summarization using Deep Learning: A Study on Automatic Summarization. 4(4). 216–226. 1 indexed citations
3.
Saqib, Muhammad. (2025). Optimizing Spot Instance Reliability and Security Using Cloud-Native Data and Tools. Journal of Information Systems Engineering & Management. 10(14s). 720–731.
4.
5.
Acharya, Debaditya, et al.. (2024). Using deep learning to automate the detection of bird scaring lines on fishing vessels. Biological Conservation. 296. 110713–110713. 2 indexed citations
6.
Saqib, Muhammad, et al.. (2024). Fishing event detection and species classification using computer vision and artificial intelligence for electronic monitoring. Fisheries Research. 280. 107141–107141. 8 indexed citations
7.
Fu, Weina, Shuai Liu, Saeed Anwar, et al.. (2024). Cefdet: Cognitive Effectiveness Network Based on Fuzzy Inference for Action Detection. 7985–7994. 2 indexed citations
8.
Saqib, Muhammad, et al.. (2024). Enhanced Atrous Spatial Pyramid Pooling Feature Fusion for Small Ship Instance Segmentation. Journal of Imaging. 10(12). 299–299. 2 indexed citations
9.
Saqib, Muhammad, et al.. (2024). MASSNet: Multiscale Attention for Single-Stage Ship Instance Segmentation. Neurocomputing. 594. 127830–127830. 11 indexed citations
10.
Saqib, Muhammad, Muhammad Aqib, Muhammad Naveed Tahir, & Yaser Hafeez. (2023). Towards deep learning based smart farming for intelligent weeds management in crops. Frontiers in Plant Science. 14. 1211235–1211235. 18 indexed citations
11.
Saqib, Muhammad, et al.. (2023). Risk Prediction of Thalassemia Using Data Mining Classifiers. 2(2). 97–109.
12.
Saqib, Muhammad, et al.. (2022). COVID-19 Detection from Radiographs: Is Deep Learning Able to Handle the Crisis?. SHILAP Revista de lepidopterología. 3(2). 296–312. 6 indexed citations
13.
Tahir, Muhammad, et al.. (2022). Image Aesthetic Assessment: A Comparative Study of Hand-Crafted & Deep Learning Models. IEEE Access. 10. 101770–101789. 1 indexed citations
14.
Chaturvedi, Kunal, Ali Braytee, Dinesh Kumar Vishwakarma, et al.. (2021). Automated Threat Objects Detection with Synthetic Data for Real-Time X-ray Baggage Inspection. 1–8. 7 indexed citations
15.
Saqib, Muhammad, et al.. (2020). Subspace Gaussian Mixture Model for Continuous Urdu Speech Recognition using Kaldi. 1–7. 7 indexed citations
16.
Saqib, Muhammad, Sultan Daud Khan, Nabin Sharma, et al.. (2018). Real-Time Drone Surveillance and Population Estimation of Marine Animals from Aerial Imagery. 1–6. 17 indexed citations
17.
Das, Abhijit, et al.. (2018). More Realistic and Efficient Face-Based Mobile Authentication using CNNs. Griffith Research Online (Griffith University, Queensland, Australia). 1–8.
18.
Coluccia, Angelo, Geert De Cubber, Arne Schumann, et al.. (2017). Drone-vs-Bird detection challenge at IEEE AVSS2017. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 1–6. 37 indexed citations
19.
Saqib, Muhammad, Sultan Daud Khan, & Michael Blumenstein. (2016). Texture-based feature mining for crowd density estimation: A study. Griffith Research Online (Griffith University, Queensland, Australia). 1–6. 12 indexed citations
20.
Arif, Muhammad, et al.. (2012). Counting of Moving People in the Video using Neural Network System. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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